Systems and methods for detecting malicious files

ABSTRACT

A computer-implemented method for detecting malicious files may include determining that a file on a client system may be subject to a security assessment, generating an initial fingerprint of the file, the generation of the initial fingerprint excluding at least part of the file, sending the initial fingerprint to a server and receiving a response from the server including an indication that the initial fingerprint matches at least one known malicious file but that the file from which the initial fingerprint was generated may not match the malicious file, generating an additional hash of the file on the client system based at least in part on the part of the file excluded in the generation of the initial fingerprint, sending the additional hash to the server, and receiving a response indicating that the file on the client system is malicious. Various other methods, systems, and computer-readable media are also disclosed.

BACKGROUND

Malicious files have long been a problem in computing, and that problemonly continues to grow. Constant internet connectivity and a plethora offile transfer devices create ever more opportunities for malicious filesto find their way to users' computers.

Some traditional anti-malware systems keep signature databases of allknown malware variants, but as the number of these variants increases,these databases grow to unwieldy sizes. In order to relieve clientsystems of the burden of storing and updating large anti-malwaredatabases, some traditional anti-malware systems may use cloud-basedmalware lookups. For example, some traditional anti-malware systems maycompute full file hashes to match against cloud-based malware databases.Unfortunately, these traditional anti-malware systems may require thatcomputationally expensive full-file hashes be computed for each file ona client system before that file can be looked up in the cloud database.This additional computational burden may slow down the client, reducingthe benefit of hosting the fingerprints in a cloud-based database.Accordingly, the instant disclosure identifies and addresses a need foradditional and improved systems and methods for detecting maliciousfiles.

SUMMARY

As will be described in greater detail below, the instant disclosuregenerally relates to systems and methods for detecting malicious filesby generating an initial partial fingerprint of a file on a clientsystem, sending the initial partial fingerprint to a server andreceiving a response indicating that the file may be malicious, sendingan additional (e.g., more definitive) hash to the server, and receivinga response indicating the file is malicious. In some examples, thesesystems and methods may generate the additional hash in only a fractionof all cases, minimizing resource-intensive client full-file hashingoperations.

In one example a computer-implemented method for detecting maliciousfiles may include (1) determining that a file on a client system may besubject to a security assessment, (2) based on determining that the filemay be subject to the security assessment, generating an initialfingerprint of the file on the client system, the generation of theinitial fingerprint excluding at least a part of the file, (3) sendingthe initial fingerprint to a server and receiving a response from theserver including an indication that the initial fingerprint matches atleast one known malicious file but that the file from which the initialfingerprint was generated may not match the malicious file, (4)generating, in response to the indication, an additional hash of thefile on the client system based at least in part on the part of the fileexcluded in the generation of the initial fingerprint, and (5) sendingthe additional hash to the server and receiving an additional responsefrom the server indicating that the file on the client system ismalicious.

In some embodiments the computer-implemented method may includeperforming a security action on the file based on the additionalresponse indicating that the file is malicious. In these examplesperforming the security action on the file may include (1) deleting thefile, (2) quarantining the file, and/or (3) alerting a user that thefile may be malicious.

In one embodiment the computer-implemented method may further include(1) determining that a second file on the client system may be subjectto a second security assessment, (2) based on determining that thesecond file may be subject to the second security assessment, generatinga second initial fingerprint of the second file on the client system,the generation of the second initial fingerprint excluding at least asecond part of the second file, (3) sending the second initialfingerprint to the server and receiving a second response from theserver including a second indication that the second initial fingerprintmay match at least one malicious file and (4) determining, based on thesecond indication, that the second file on the client system may bemalicious.

In one embodiment the indication may include a false positive rate forthe initial fingerprint; the false positive rate may be the probabilitythat the additional hash will not match any malicious files.

In one embodiment the false positive rate may be determined by a ratioof known malicious files that the initial fingerprint matches to filesnot known to be malicious that the initial fingerprint matches.

In one embodiment the false positive rate may be determined by ahistorical percentage of accurate matches for the initial fingerprint.

In one embodiment the additional hash may represent a larger portion ofthe file than the initial fingerprint represents.

In one embodiment the part of the file may include (1) content withinthe file, (2) a size of the file, (3) a timestamp of the file and/or (4)header data of the file.

In one embodiment a system for implementing the above-described methodmay include (1) a determination module programmed to determine that afile on a client system may be subject to a security assessment, (2)based on determining that the file may be subject to the securityassessment, a generation module may be programmed to generate an initialfingerprint of the file on the client system, the generation of theinitial fingerprint excluding at least a part of the file, (3) a sendingmodule programmed to send the initial fingerprint to a server and areceiving module programmed to receive a response from the serverincluding an indication that the initial fingerprint matches at leastone known malicious file but that the file from which the initialfingerprint was generated may not match the malicious file, (4) thegeneration module may be programmed to generate, in response to theindication, an additional hash of the file on the client system based atleast in part on the part of the file excluded in the generation of theinitial fingerprint, (5) the sending module may be programmed to sendthe additional hash to the server and the receiving module may beprogrammed to receive an additional response from the server indicatingthat the file on the client system is malicious and (6) at least oneprocessor configured to execute the determination module, the sendingmodule, the receiving module and the generation module.

In some examples the above-described method may be encoded ascomputer-readable instructions on a computer-readable-storage medium.For example, a computer-readable-storage medium may include one or morecomputer-executable instructions that, when executed by at least oneprocessor of a computing device, may cause the computing device to (1)determine that a file on a client system is subject to a securityassessment, (2) send the initial fingerprint to a server and receive aresponse from the server including an indication that the initialfingerprint matches at least one known malicious file but that the filefrom which the initial fingerprint was generated may not match themalicious file, (3) generate, in response to the indication, anadditional hash of the file on the client system based at least in parton the part of the file excluded in the generation of the initialfingerprint, and (4) send the additional hash to the server and receivean additional response from the server indicating that the file on theclient system is malicious.

Features from any of the above-mentioned embodiments may be used incombination with one another in accordance with the general principlesdescribed herein. These and other embodiments, features, and advantageswill be more fully understood upon reading the following detaileddescription in conjunction with the accompanying drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings illustrate a number of exemplary embodimentsand are a part of the specification. Together with the followingdescription, these drawings demonstrate and explain various principlesof the instant disclosure.

FIG. 1 is a block diagram of an exemplary system for detecting maliciousfiles.

FIG. 2 is a block diagram of an exemplary system for detecting maliciousfiles.

FIG. 3 is a flow diagram of an exemplary method for detecting maliciousfiles.

FIG. 4 is a block diagram of an exemplary system for detecting maliciousfiles.

FIG. 5 is a diagram of exemplary file parts.

FIG. 6 is a block diagram of an exemplary computing system capable ofimplementing one or more of the embodiments described and/or illustratedherein.

FIG. 7 is a block diagram of an exemplary computing network capable ofimplementing one or more of the embodiments described and/or illustratedherein.

Throughout the drawings, identical reference characters and descriptionsindicate similar, but not necessarily identical, elements. While theexemplary embodiments described herein are susceptible to variousmodifications and alternative forms, specific embodiments have beenshown by way of example in the drawings and will be described in detailherein. However, the exemplary embodiments described herein are notintended to be limited to the particular forms disclosed. Rather, theinstant disclosure covers all modifications, equivalents, andalternatives falling within the scope of the appended claims.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The present disclosure is generally directed to systems and methods fordetecting malicious files. As will be explained in greater detail below,by initially sending a partial fingerprint of the file and only sendinga full and/or more complete hash after receiving an indication that thefile may be malicious, the systems and methods described herein maydetect a malicious file more quickly and/or with fewerresource-intensive file operations on average without sacrificingdetection accuracy.

The following will provide, with reference to FIGS. 1-2 and 4, detaileddescriptions of exemplary systems for detecting malicious files.Detailed descriptions of corresponding computer-implemented methods willalso be provided in connection with FIG. 3. Detailed descriptions ofexemplary file parts will be provided in FIG. 5. In addition, detaileddescriptions of an exemplary computing system and network architecturecapable of implementing one or more of the embodiments described hereinwill be provided in connection with FIGS. 6 and 7, respectively.

FIG. 1 is a block diagram of exemplary system 100 for detectingmalicious files. As illustrated in this figure, exemplary system 100 mayinclude one or more modules 102 for performing one or more tasks. Forexample, and as will be explained in greater detail below, exemplarysystem 100 may also include a determination module 104 programmed todetermine that a file on a client system may be subject to a securityassessment. Exemplary system 100 may additionally include a generationmodule 106 programmed to, based on determining that the file is subjectto the security assessment, generate an initial fingerprint of the fileon the client system, the generation of the initial fingerprintexcluding at least a part of the file. Exemplary system 100 mayadditionally include a sending module 108 programmed to send the initialfingerprint to a server. Exemplary system 100 may also include areceiving module 110 programmed to receive a response from the serverincluding an indication that the initial fingerprint an indication thatthe initial fingerprint matches at least one known malicious file butthat the file from which the initial fingerprint was generated may notmatch the malicious file.

Generation module 106 may be further programmed to generate, in responseto the indication, an additional hash of the file on the client systembased at least in part on the part of the file excluded in thegeneration of the initial fingerprint. Sending module 108 may be furtherprogrammed to send the additional hash to the server. Receiving module110 may be further programmed to receive an additional response from theserver indicating that the file on the client system is malicious.Although illustrated as separate elements, one or more of modules 102 inFIG. 1 may represent portions of a single module or application.

In certain embodiments one or more of modules 102 in FIG. 1 mayrepresent one or more software applications or programs that, whenexecuted by a computing device, may cause the computing device toperform one or more tasks. For example, and as will be described ingreater detail below, one or more of modules 102 may represent softwaremodules stored and configured to run on one or more computing devices,such as the devices illustrated in FIG. 2 (e.g., computing device 202and/or server 206), computing system 610 in FIG. 6, and/or portions ofexemplary network architecture 700 in FIG. 7. One or more of modules 102in FIG. 1 may also represent all or portions of one or morespecial-purpose computers configured to perform one or more tasks.

Exemplary system 100 in FIG. 1 may be implemented in a variety of ways.For example, all or a portion of exemplary system 100 may representportions of exemplary system 200 in FIG. 2. As shown in FIG. 2, system200 may include a computing device 202 in communication with a server206 via a network 204. Additionally or alternatively, server 206 may beprogrammed with one or more of modules 102.

In one embodiment one or more of modules 102 from FIG. 1 may, whenexecuted by at least one processor of computing device 202 and/or server206, facilitate computing device 202 and/or server 206 in detectingmalicious files. For example, and as will be described in greater detailbelow, one or more of modules 102 may cause computing device 202 and/orserver 206 to detect malicious files. For example, and as will bedescribed in greater detail below, determination module 104 may beprogrammed to determine that a file 208 on a computing device 202 issubject to a security assessment. Generation module 106 may beprogrammed to generate a limited fingerprint 210 of file 208 oncomputing device 202, the generation of fingerprint 210 excluding atleast a part of file 208. Sending module 108 may be programmed to sendfingerprint 210 to a server 206 and receiving module 110 may beprogrammed to receive a response 214 from server 206 which may includean indication 220 that fingerprint 210 may match at least one knownmalicious file 218 but that the file from which fingerprint 210 wasgenerated (e.g., file 208) may not match malicious file 218. Generationmodule 106 may be further programmed to generate, in response toindication 220, a hash 212 of file 208 on computing device 202 based atleast in part on the part of file 208 excluded in the generation offingerprint 210. Sending module 108 may be further programmed to sendhash 212 to server 206 and receiving module 110 may be programmed toreceive a response 216 from server 206 indicating that file 208 oncomputing device 202 may be malicious file 218.

In some embodiments security module 222 may perform a security actionbased on determining that file 208 may match malicious file 218. In someexamples the security action may include deleting file 208, quarantiningfile 208, and/or alerting a user that file 208 may be malicious.

In some embodiments indication 220 may include a false positive rate.The phrase “false positive rate,” when used herein, may in some examplesrefer to the probability and/or rate at which that the file may notmatch any known malicious files. In some examples the false positiverate may be determined by a ratio of known malicious files that the hashmay match to files not known to be malicious that the hash may match. Insome examples the false positive rate may be determined by a historicalpercentage of accurate matches for the hash.

Computing device 202 generally represents any type or form of computingdevice capable of reading computer-executable instructions. Examples ofcomputing device 202 include, without limitation, laptops, tablets,desktops, servers, cellular phones, Personal Digital Assistants (PDAs),multimedia players, embedded systems, combinations of one or more of thesame, exemplary computing system 610 in FIG. 6, or any other suitablecomputing device.

Server 206 generally represents any type or form of computing devicethat is capable of comparing file hashes. Examples of server 206include, without limitation, application servers and database serversconfigured to provide various database services and/or run certainsoftware applications.

Network 204 generally represents any medium or architecture capable offacilitating communication or data transfer. Examples of network 204include, without limitation, an intranet, a Wide Area Network (WAN), aLocal Area Network (LAN), a Storage Area Network (SAN), a Personal AreaNetwork (PAN), the Internet, Power Line Communications (PLC), a cellularnetwork (e.g., a Global System for Mobile Communications (GSM) network),exemplary network architecture 700 in FIG. 7, or the like. Network 204may facilitate communication or data transfer using wireless or wiredconnections. In one embodiment, network 204 may facilitate communicationbetween computing device 202 and server 206.

FIG. 3 is a flow diagram of an exemplary computer-implemented method 300for detecting malicious files. The steps shown in FIG. 3 may beperformed by any suitable computer-executable code and/or computingsystem. In some embodiments the steps shown in FIG. 3 may be performedby one or more of the components of system 100 in FIG. 1, system 200 inFIG. 2, computing system 610 in FIG. 6, and/or portions of exemplarynetwork architecture 700 in FIG. 7.

As illustrated in FIG. 3, at step 302 one or more of the systemsdescribed herein may determine that a file on a client system is subjectto a security assessment. For example, at step 302 determination module104 may, as part of computing device 202 in FIG. 2, determine that file208 on computing device 202 is subject to a security assessment.

As used herein, the phrase “security assessment” may refer to anysuitable security assessment, analysis, and/or scan. For example, thesecurity assessment may include a malware scan, an intrusion preventionanalysis, etc. As used herein, the term “malware” may refer to anyvirus, worm, Trojan horse, spyware, and/or any other malicious,illegitimate, and/or unauthorized software and/or data object.

Determination module 104 may determine that the file is subject to asecurity assessment in any suitable manner. For example, determinationmodule 104 may determine that the file is subject to a securityassessment while scanning the client system for malware and encounteringthe file. Additionally or alternatively, determination module 104 maydetermine that the file is subject to a security assessment based on asecurity policy that identifies the file as suspect and/or potentiallymalicious. For example, determination module 104 may determine that thefile is subject to a security assessment based on an origin of the file,a behavior originating from the file, and/or a lack of a credential onthe part of the file.

Returning to FIG. 3, at step 304 one or more of the systems describedherein may, based on determining that the file is subject to thesecurity assessment, generate an initial fingerprint of the file on theclient system, the generation of the initial fingerprint excluding atleast a part of the file. For example, at step 304 generation module 106may, as part of computing device 202 in FIG. 2, based on determiningthat file 208 is subject to the security assessment, generatefingerprint 210 of file 208 on computing device 202, the generation offingerprint 210 excluding at least a part of file 208.

As used herein, the term “fingerprint” may refer to any abbreviatedrepresentation of a file and/or the contents of a file. For example, theterm “fingerprint” may refer to the outputs of one or more hashfunctions applied to various regions of the file, values extracted fromthe file, the file size, the number of sections in the file, checksums,and/or any other type of file identifiers that identify a file and/orfile content. Generally, the fingerprint may include any informationtending to identify the file, including any of the aforementionedexamples, alone or in combination. The hash values may be generated byany of a variety of cryptographic hash functions (including, e.g., MD5and/or SHA256). In some examples, the term “fingerprint” as it relatesto a given file may refer to a single value that consistently representsthe file over time and that does not vary unless the content of the filebeing fingerprinted varies.

Generation module 106 may generate the initial fingerprint of the filein any suitable manner. For example, generation module 106 may generatehashes of multiple regions of the file (e.g., totaling no more than 100kilobytes) and combine the hashes into a single fingerprint.Additionally or alternatively, generation module 106 may identify one ormore features and/or metadata of the file (e.g., the size of the file, anumber of sections in the file, an embedded timestamp indicating whenthe file was created, the size of one or more sections of the file,and/or file header metadata, etc.) and combine these features into afingerprint. For example, generation module 106 may concatenate one ormore values derived from one or more features of the file (e.g.,“15523,72,3,456,333”) and/or generate a hash of such a concatenation. Insome examples, the initial fingerprint may represent a lightweight hash.As used herein, the phrase “lightweight hash” may refer to any hashgenerated using a limited amount of computing resources. For example,generation module 106 may generate the initial fingerprint based on alittle total amount of the file content (e.g., no more than 5 percent ofthe file content, no more than 100 kilobytes of the file content, etc.).

At step 306 one or more of the systems described herein may send theinitial fingerprint to a server and receive a response from the serverincluding an indication that the initial fingerprint matches at leastone known malicious file but that the file from which the initialfingerprint was generated may not match the malicious file. For example,at step 306 sending module 108 may, as part of computing device 202 inFIG. 2, send initial fingerprint 210 to server 206 and receiving module110 may receive response 214 from server 206 including indication 220that initial fingerprint 210 may match at least one known malicious file(e.g., including malicious file 218) but that the file from whichfingerprint 210 was generated (e.g., file 208) may not match maliciousfile 218.

Sending module 108 may send the initial fingerprint to the server in anysuitable manner. For example, sending module 108 may send the initialfingerprint to the server in the form of a database query for filesmatching the initial fingerprint. Additionally or alternatively, sendingmodule 108 may send the initial fingerprint to the server as a requestfor a determination as to whether the file is malicious.

Receiving module 110 may receive any suitable type of indication thatthe initial fingerprint matches at least one known malicious file butthat the file from which the initial fingerprint was generated may notmatch the malicious file. For example, receiving module 110 may receivea request from the server to send an additional (e.g., full and/or morecomprehensive) hash. Additionally or alternatively, receiving module 110may receive a false positive rate for the initial fingerprint. The falsepositive rate may include the probability that an additional (e.g.,definitive, full, and/or comprehensive) hash will not match anymalicious files (e.g., despite the initial fingerprint matching at leastone malicious file). Additionally or alternatively, the false positiverate may represent a ratio of known malicious files that the initialfingerprint matches to files not known to be malicious that the initialfingerprint matches. For example, the server may access a database offiles and/or file hashes (e.g., of malicious files, legitimate files,and files of unknown and/or indeterminate legitimacy). Upon receivingthe initial fingerprint from the client system, the server may query thedatabase for files matching the initial fingerprint and determine thateighteen files malicious files match the initial fingerprint and twolegitimate files match the initial fingerprint. Accordingly, the servermay determine that the initial fingerprint has a false positive rate of10%.

In some examples, the server may determine the false positive rateaccording to a historical percentage of accurate matches for the initialfingerprint. For example, the server may have received hashes identicalto the initial fingerprint on previous occasions (e.g., from variousclient systems) as well as information from the client systemsindicating whether the initial fingerprints originated from maliciousfiles (e.g., the information may include a subsequent complete hash of afile that was the source of the initial fingerprint, a copy of the file,and/or a determination from an anti-malware system that the fileexhibited malicious behavior).

In some examples, receiving module 110 may receive an indication thatthe initial fingerprint may match at least one known malicious file anddoes not match any files not known to be malicious. Additionally oralternatively, receiving module 110 may receive an indication that theinitial fingerprint is malicious with no chance and/or a negligiblechance of a false positive. In these examples, the systems and methodsdescribed herein may not generate an additional hash and may immediatelydetermine that the file may be malicious.

At step 308 one or more of the systems described herein may generate, inresponse to the indication, an additional hash of the file on the clientsystem based at least in part on the part of the file excluded in thegeneration of the initial fingerprint. For example, at step 308generation module 106 may, as part of computing device 202 in FIG. 2,generate, in response 214 to indication 220, hash 212 of file 208 onclient system 202 based at least in part on the part of file 208excluded in the generation of initial fingerprint 210.

As used herein, the term “hash” may refer to any abbreviatedrepresentation of a file and/or the contents of a file. For example, theterm “hash” may refer to the outputs of one or more hash functions,fingerprints, checksums, and/or any other type of file identifiers thatuniquely identify a file and/or file content (barring a collision). Forexample, the hash may be generated by any of a variety of cryptographichash functions (including, e.g., MD5 and/or SHA256).

Generation module 106 may generate the additional hash in any suitablemanner. For example, generation module 106 may generate the additionalhash by generating a complete hash of the file. Additionally oralternatively, generation module 106 may generate the additional hash bygenerating a hash of only the portions of the file not used in thegeneration of the initial fingerprint. In some examples, generationmodule 106 may generate the additional hash by generating andconcatenating one or more hashes of unique portions of the file thatwere too large to process for a lightweight fingerprint.

At step 310 one or more of the systems described herein may send theadditional hash to the server and receive an additional response fromthe server indicating that the file on the client system is malicious.For example, at step 310 sending module 108 may, as part of computingdevice 202 in FIG. 2, send hash 212 to server 206 and receiving module110 may receive a response 216 from server 206 indicating that file 208on computing device 202 is malicious file 218.

Sending module 108 may send the additional hash to the server in anysuitable manner. For example, sending module 108 may send the additionalhash to the server in the form of a database query for files matchingthe additional hash. Additionally or alternatively, sending module 108may send the additional hash to the server as a request for adetermination as to whether the file is malicious.

Receiving module 110 may receive the additional response in any suitableformat. For example, the additional response may include acategorization of the file as malicious. Additionally or alternatively,the additional response may include an instruction to the client systemfor handling the file.

In some examples, after receiving the additional response indicatingthat the file is malicious, one or more of the systems described herein(e.g., security module 222) may perform a security action on the filebased on the additional response. For example, security module 222 maydelete the file, quarantine the file, and/or alert a user that the fileis malicious.

FIG. 4 is a block diagram of an exemplary computing system 400 fordetecting malicious files. In some examples server 406 may containmalicious file 218, file 410 and/or file 420. In these examplesfingerprint 408 and/or hash 418 may represent malicious file 218,fingerprint 412 and/or hash 414 may represent file 410, and/orfingerprint 416 and/or hash 422 may represent file 420. In theseexamples hash 418 may represent a larger portion of malicious file 218than fingerprint 408 may represent. In some examples if fingerprint 408matches the initial fingerprint generated by the client system then hash418 may match the additional hash generated by the client system.

FIG. 5 is a diagram of an exemplary set of file parts 500. As shown inFIG. 5, a file 502 may include various file parts, including file parts512, 514, 516, 520, and 522. In some examples fingerprint 210 may becalculated from file part 512, file part 514 and file part 516, and hash212 may be calculated from file part 520 and file part 522. Additionallyor alternatively, hash 212 may be calculated from the entirety of file502. In these examples, hash 212 may include a larger portion of thefile than fingerprint 210. In some embodiments a file part may representcontent within the file, the size of the file, the timestamp of thefile, and/or a piece of header data of the file.

As explained above in connection with method 300 in FIG. 3, a file on aclient system may be subject to a security assessment. Instead ofgenerating a full hash of the file and submitting the full hash to acloud-based security server, the client system may generate alightweight fingerprint representing the file and send it to the server.The client system may receive a response from the server indicating thatthe lightweight fingerprint may match one or more files known to bemalicious, but that the lightweight fingerprint proved insufficient toconclusively determine that the file is malicious. The client system maythen generate an additional hash representing a larger portion of thefile than the initial fingerprint, and send the additional hash to theserver. The client system may receive a response from the serverindicating that the file almost certainly is malicious and/or matchesexclusively malicious files, and may determine that the file ismalicious. The client may then take a security action based on thedetermination. By first attempting to use a lightweight fingerprint todetermine whether the file is malicious, the systems and methodsdescribed herein may avoid resource-intensive operations in asignificant proportion of cases (e.g., 98 or 99 out of 100 file scans).

FIG. 6 is a block diagram of an exemplary computing system 610 capableof implementing one or more of the embodiments described and/orillustrated herein. For example, all or a portion of computing system610 may perform and/or be a means for performing, either alone or incombination with other elements, one or more of the determining,generating, sending, receiving, performing, deleting, quarantining,and/or alerting steps described herein. All or a portion of computingsystem 610 may also perform and/or be a means for performing any othersteps, methods, or processes described and/or illustrated herein.

Computing system 610 broadly represents any single or multi-processorcomputing device or system capable of executing computer-readableinstructions. Examples of computing system 610 include, withoutlimitation, workstations, laptops, client-side terminals, servers,distributed computing systems, handheld devices, or any other computingsystem or device. In its most basic configuration, computing system 610may include at least one processor 614 and a system memory 616.

Processor 614 generally represents any type or form of processing unitcapable of processing data or interpreting and executing instructions.In certain embodiments, processor 614 may receive instructions from asoftware application or module. These instructions may cause processor614 to perform the functions of one or more of the exemplary embodimentsdescribed and/or illustrated herein.

System memory 616 generally represents any type or form of volatile ornon-volatile storage device or medium capable of storing data and/orother computer-readable instructions. Examples of system memory 616include, without limitation, Random Access Memory (RAM), Read OnlyMemory (ROM), flash memory, or any other suitable memory device.Although not required, in certain embodiments computing system 610 mayinclude both a volatile memory unit (such as, for example, system memory616) and a non-volatile storage device (such as, for example, primarystorage device 632, as described in detail below). In one example, oneor more of modules 102 from FIG. 1 may be loaded into system memory 616.

In certain embodiments, exemplary computing system 610 may also includeone or more components or elements in addition to processor 614 andsystem memory 616. For example, as illustrated in FIG. 6, computingsystem 610 may include a memory controller 618, an Input/Output (I/O)controller 620, and a communication interface 622, each of which may beinterconnected via a communication infrastructure 612. Communicationinfrastructure 612 generally represents any type or form ofinfrastructure capable of facilitating communication between one or morecomponents of a computing device. Examples of communicationinfrastructure 612 include, without limitation, a communication bus(such as an Industry Standard Architecture (ISA), Peripheral ComponentInterconnect (PCI), PCI Express (PCIe), or similar bus) and a network.

Memory controller 618 generally represents any type or form of devicecapable of handling memory or data or controlling communication betweenone or more components of computing system 610. For example, in certainembodiments memory controller 618 may control communication betweenprocessor 614, system memory 616, and I/O controller 620 viacommunication infrastructure 612.

I/O controller 620 generally represents any type or form of modulecapable of coordinating and/or controlling the input and outputfunctions of a computing device. For example, in certain embodiments I/Ocontroller 620 may control or facilitate transfer of data between one ormore elements of computing system 610, such as processor 614, systemmemory 616, communication interface 622, display adapter 626, inputinterface 630, and storage interface 634.

Communication interface 622 broadly represents any type or form ofcommunication device or adapter capable of facilitating communicationbetween exemplary computing system 610 and one or more additionaldevices. For example, in certain embodiments communication interface 622may facilitate communication between computing system 610 and a privateor public network including additional computing systems. Examples ofcommunication interface 622 include, without limitation, a wired networkinterface (such as a network interface card), a wireless networkinterface (such as a wireless network interface card), a modem, and anyother suitable interface. In at least one embodiment, communicationinterface 622 may provide a direct connection to a remote server via adirect link to a network, such as the Internet. Communication interface622 may also indirectly provide such a connection through, for example,a local area network (such as an Ethernet network), a personal areanetwork, a telephone or cable network, a cellular telephone connection,a satellite data connection, or any other suitable connection.

In certain embodiments, communication interface 622 may also represent ahost adapter configured to facilitate communication between computingsystem 610 and one or more additional network or storage devices via anexternal bus or communications channel. Examples of host adaptersinclude, without limitation, Small Computer System Interface (SCSI) hostadapters, Universal Serial Bus (USB) host adapters, Institute ofElectrical and Electronics Engineers (IEEE) 1394 host adapters, AdvancedTechnology Attachment (ATA), Parallel ATA (PATA), Serial ATA (SATA), andExternal SATA (eSATA) host adapters, Fibre Channel interface adapters,Ethernet adapters, or the like. Communication interface 622 may alsoallow computing system 610 to engage in distributed or remote computing.For example, communication interface 622 may receive instructions from aremote device or send instructions to a remote device for execution.

As illustrated in FIG. 6, computing system 610 may also include at leastone display device 624 coupled to communication infrastructure 612 via adisplay adapter 626. Display device 624 generally represents any type orform of device capable of visually displaying information forwarded bydisplay adapter 626. Similarly, display adapter 626 generally representsany type or form of device configured to forward graphics, text, andother data from communication infrastructure 612 (or from a framebuffer, as known in the art) for display on display device 624.

As illustrated in FIG. 6, exemplary computing system 610 may alsoinclude at least one input device 628 coupled to communicationinfrastructure 612 via an input interface 630. Input device 628generally represents any type or form of input device capable ofproviding input, either computer or human generated, to exemplarycomputing system 610. Examples of input device 628 include, withoutlimitation, a keyboard, a pointing device, a speech recognition device,or any other input device.

As illustrated in FIG. 6, exemplary computing system 610 may alsoinclude a primary storage device 632 and a backup storage device 633coupled to communication infrastructure 612 via a storage interface 634.Storage devices 632 and 633 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions. For example, storage devices 632 and 633may be a magnetic disk drive (e.g., a so-called hard drive), a solidstate drive, a floppy disk drive, a magnetic tape drive, an optical diskdrive, a flash drive, or the like. Storage interface 634 generallyrepresents any type or form of interface or device for transferring databetween storage devices 632 and 633 and other components of computingsystem 610.

In certain embodiments, storage devices 632 and 633 may be configured toread from and/or write to a removable storage unit configured to storecomputer software, data, or other computer-readable information.Examples of suitable removable storage units include, withoutlimitation, a floppy disk, a magnetic tape, an optical disk, a flashmemory device, or the like. Storage devices 632 and 633 may also includeother similar structures or devices for allowing computer software,data, or other computer-readable instructions to be loaded intocomputing system 610. For example, storage devices 632 and 633 may beconfigured to read and write software, data, or other computer-readableinformation. Storage devices 632 and 633 may also be a part of computingsystem 610 or may be a separate device accessed through other interfacesystems.

Many other devices or subsystems may be connected to computing system610. Conversely, all of the components and devices illustrated in FIG. 6need not be present to practice the embodiments described and/orillustrated herein. The devices and subsystems referenced above may alsobe interconnected in different ways from that shown in FIG. 6. Computingsystem 610 may also employ any number of software, firmware, and/orhardware configurations. For example, one or more of the exemplaryembodiments disclosed herein may be encoded as a computer program (alsoreferred to as computer software, software applications,computer-readable instructions, or computer control logic) on acomputer-readable-storage medium. The phrase “computer-readable-storagemedium” generally refers to any form of device, carrier, or mediumcapable of storing or carrying computer-readable instructions. Examplesof computer-readable-storage media include, without limitation,transmission-type media, such as carrier waves, and non-transitory-typemedia, such as magnetic-storage media (e.g., hard disk drives and floppydisks), optical-storage media (e.g., Compact Disks (CDs) or DigitalVideo Disks (DVDs)), electronic-storage media (e.g., solid-state drivesand flash media), and other distribution systems.

The computer-readable-storage medium containing the computer program maybe loaded into computing system 610. All or a portion of the computerprogram stored on the computer-readable-storage medium may then bestored in system memory 616 and/or various portions of storage devices632 and 633. When executed by processor 614, a computer program loadedinto computing system 610 may cause processor 614 to perform and/or be ameans for performing the functions of one or more of the exemplaryembodiments described and/or illustrated herein. Additionally oralternatively, one or more of the exemplary embodiments described and/orillustrated herein may be implemented in firmware and/or hardware. Forexample, computing system 610 may be configured as an ApplicationSpecific Integrated Circuit (ASIC) adapted to implement one or more ofthe exemplary embodiments disclosed herein.

FIG. 7 is a block diagram of an exemplary network architecture 700 inwhich client systems 710, 720, and 730 and servers 740 and 745 may becoupled to a network 750. As detailed above, all or a portion of networkarchitecture 700 may perform and/or be a means for performing, eitheralone or in combination with other elements, one or more of thedetermining, generating, sending, receiving, performing, deleting,quarantining, and/or alerting steps disclosed herein. All or a portionof network architecture 700 may also be used to perform and/or be ameans for performing other steps and features set forth in the instantdisclosure.

Client systems 710, 720, and 730 generally represent any type or form ofcomputing device or system, such as exemplary computing system 610 inFIG. 6. Similarly, servers 740 and 745 generally represent computingdevices or systems, such as application servers or database servers,configured to provide various database services and/or run certainsoftware applications. Network 750 generally represents anytelecommunication or computer network including, for example, anintranet, a WAN, a LAN, a PAN, or the Internet. In one example, clientsystems 710, 720, and/or 730 and/or servers 740 and/or 745 may includeall or a portion of system 100 from FIG. 1.

As illustrated in FIG. 7, one or more storage devices 760(1)-(N) may bedirectly attached to server 740. Similarly, one or more storage devices770(1)-(N) may be directly attached to server 745. Storage devices760(1)-(N) and storage devices 770(1)-(N) generally represent any typeor form of storage device or medium capable of storing data and/or othercomputer-readable instructions. In certain embodiments, storage devices760(1)-(N) and storage devices 770(1)-(N) may represent Network-AttachedStorage (NAS) devices configured to communicate with servers 740 and 745using various protocols, such as Network File System (NFS), ServerMessage Block (SMB), or Common Internet File System (CIFS).

Servers 740 and 745 may also be connected to a Storage Area Network(SAN) fabric 780. SAN fabric 780 generally represents any type or formof computer network or architecture capable of facilitatingcommunication between a plurality of storage devices. SAN fabric 780 mayfacilitate communication between servers 740 and 745 and a plurality ofstorage devices 790(1)-(N) and/or an intelligent storage array 795. SANfabric 780 may also facilitate, via network 750 and servers 740 and 745,communication between client systems 710, 720, and 730 and storagedevices 790(1)-(N) and/or intelligent storage array 795 in such a mannerthat devices 790(1)-(N) and array 795 appear as locally attached devicesto client systems 710, 720, and 730. As with storage devices 760(1)-(N)and storage devices 770(1)-(N), storage devices 790(1)-(N) andintelligent storage array 795 generally represent any type or form ofstorage device or medium capable of storing data and/or othercomputer-readable instructions.

In certain embodiments, and with reference to exemplary computing system610 of FIG. 6, a communication interface, such as communicationinterface 622 in FIG. 6, may be used to provide connectivity betweeneach client system 710, 720, and 730 and network 750. Client systems710, 720, and 730 may be able to access information on server 740 or 745using, for example, a web browser or other client software. Suchsoftware may allow client systems 710, 720, and 730 to access datahosted by server 740, server 745, storage devices 760(1)-(N), storagedevices 770(1)-(N), storage devices 790(1)-(N), or intelligent storagearray 795. Although FIG. 7 depicts the use of a network (such as theInternet) for exchanging data, the embodiments described and/orillustrated herein are not limited to the Internet or any particularnetwork-based environment.

In at least one embodiment, all or a portion of one or more of theexemplary embodiments disclosed herein may be encoded as a computerprogram and loaded onto and executed by server 740, server 745, storagedevices 760(1)-(N), storage devices 770(1)-(N), storage devices790(1)-(N), intelligent storage array 795, or any combination thereof.All or a portion of one or more of the exemplary embodiments disclosedherein may also be encoded as a computer program, stored in server 740,run by server 745, and distributed to client systems 710, 720, and 730over network 750.

As detailed above, computing system 610 and/or one or more components ofnetwork architecture 700 may perform and/or be a means for performing,either alone or in combination with other elements, one or more steps ofan exemplary method for detecting malicious files.

While the foregoing disclosure sets forth various embodiments usingspecific block diagrams, flowcharts, and examples, each block diagramcomponent, flowchart step, operation, and/or component described and/orillustrated herein may be implemented, individually and/or collectively,using a wide range of hardware, software, or firmware (or anycombination thereof) configurations. In addition, any disclosure ofcomponents contained within other components should be consideredexemplary in nature since many other architectures can be implemented toachieve the same functionality.

In some examples, all or a portion of exemplary system 100 in FIG. 1 mayrepresent portions of a cloud-computing or network-based environment.Cloud-computing environments may provide various services andapplications via the Internet. These cloud-based services (e.g.,software as a service, platform as a service, infrastructure as aservice, etc.) may be accessible through a web browser or other remoteinterface. Various functions described herein may be provided through aremote desktop environment or any other cloud-based computingenvironment.

In various embodiments, all or a portion of exemplary system 100 in FIG.1 may facilitate multi-tenancy within a cloud-based computingenvironment. In other words, the software modules described herein mayconfigure a computing system (e.g., a server) to facilitatemulti-tenancy for one or more of the functions described herein. Forexample, one or more of the software modules described herein mayprogram a server to enable two or more clients (e.g., customers) toshare an application that is running on the server. A server programmedin this manner may share an application, operating system, processingsystem, and/or storage system among multiple customers (i.e., tenants).One or more of the modules described herein may also partition dataand/or configuration information of a multi-tenant application for eachcustomer such that one customer cannot access data and/or configurationinformation of another customer.

According to various embodiments, all or a portion of exemplary system100 in FIG. 1 may be implemented within a virtual environment. Forexample, modules and/or data described herein may reside and/or executewithin a virtual machine. As used herein, the phrase “virtual machine”generally refers to any operating system environment that is abstractedfrom computing hardware by a virtual machine manager (e.g., ahypervisor). Additionally or alternatively, the modules and/or datadescribed herein may reside and/or execute within a virtualizationlayer. As used herein, the phrase “virtualization layer” generallyrefers to any data layer and/or application layer that overlays and/oris abstracted from an operating system environment. A virtualizationlayer may be managed by a software virtualization solution (e.g., a filesystem filter) that presents the virtualization layer as though it werepart of an underlying base operating system. For example, a softwarevirtualization solution may redirect calls that are initially directedto locations within a base file system and/or registry to locationswithin a virtualization layer.

The process parameters and sequence of steps described and/orillustrated herein are given by way of example only and can be varied asdesired. For example, while the steps illustrated and/or describedherein may be shown or discussed in a particular order, these steps donot necessarily need to be performed in the order illustrated ordiscussed. The various exemplary methods described and/or illustratedherein may also omit one or more of the steps described or illustratedherein or include additional steps in addition to those disclosed.

While various embodiments have been described and/or illustrated hereinin the context of fully functional computing systems, one or more ofthese exemplary embodiments may be distributed as a program product in avariety of forms, regardless of the particular type ofcomputer-readable-storage media used to actually carry out thedistribution. The embodiments disclosed herein may also be implementedusing software modules that perform certain tasks. These softwaremodules may include script, batch, or other executable files that may bestored on a computer-readable storage medium or in a computing system.In some embodiments, these software modules may configure a computingsystem to perform one or more of the exemplary embodiments disclosedherein.

In addition, one or more of the modules described herein may transformdata, physical devices, and/or representations of physical devices fromone form to another. For example, one or more of the modules recitedherein may receive a file to be transformed, transform the file, outputa result of the transformation to the sending module, use the result ofthe transformation to generate a hash, and store the result of thetransformation to memory. Additionally or alternatively, one or more ofthe modules recited herein may transform a processor, volatile memory,non-volatile memory, and/or any other portion of a physical computingdevice from one form to another by executing on the computing device,storing data on the computing device, and/or otherwise interacting withthe computing device.

The preceding description has been provided to enable others skilled inthe art to best utilize various aspects of the exemplary embodimentsdisclosed herein. This exemplary description is not intended to beexhaustive or to be limited to any precise form disclosed. Manymodifications and variations are possible without departing from thespirit and scope of the instant disclosure. The embodiments disclosedherein should be considered in all respects illustrative and notrestrictive. Reference should be made to the appended claims and theirequivalents in determining the scope of the instant disclosure.

Unless otherwise noted, the terms “a” or “an,” as used in thespecification and claims, are to be construed as meaning “at least oneof.” In addition, for ease of use, the words “including” and “having,”as used in the specification and claims, are interchangeable with andhave the same meaning as the word “comprising.”

What is claimed is:
 1. A computer-implemented method for detectingmalicious files, at least a portion of the method being performed by acomputing device comprising at least one processor, the methodcomprising: determining that a file previously stored on a client systemis subject to a security assessment; based on determining that the fileis subject to the security assessment, generating an initial fingerprintof the file on the client system, the generation of the initialfingerprint excluding at least a part of the file; sending, from theclient system, the initial fingerprint to a server and receiving aresponse from the server comprising an indication that the initialfingerprint matches at least one known malicious file but that the filefrom which the initial fingerprint was generated may not match themalicious file; generating, in response to the indication, an additionalfingerprint of the file on the client system based at least in part onthe part of the file excluded in the generation of the initialfingerprint; sending, from the client system, the additional fingerprintto the server and receiving an additional response from the serverindicating that the file on the client system is malicious; determiningthat a second file previously stored on the client system is subject toa second security assessment; based on determining that the second fileis subject to the second security assessment, generating a secondinitial fingerprint of the second file on the client system, thegeneration of the second initial fingerprint excluding at least a secondpart of the second file; sending, from the client system, the secondinitial fingerprint to the server and receiving a second response fromthe server comprising a second indication that the second initialfingerprint matches at least one malicious file; determining, based onthe second indication, despite the second part of the second file beingexcluded from the generation of the second initial fingerprint, andwithout generating a further fingerprint of the second file aftergenerating the second initial fingerprint, that the second file on theclient system is malicious.
 2. The computer-implemented method of claim1, further comprising performing a security action on the file based onthe additional response indicating that the file is malicious.
 3. Thecomputer-implemented method of claim 2, wherein performing the securityaction on the file comprises at least one of: deleting the file;quarantining the file; alerting a user that the file is malicious. 4.The computer-implemented method of claim 1, wherein the indication thatthe initial fingerprint matches the at least one known malicious filecomprises a false positive rate for the initial fingerprint, the falsepositive rate comprising the probability that the additional fingerprintwill not match any malicious files.
 5. The computer-implemented methodof claim 4, wherein the false positive rate is determined by a ratio ofknown malicious files that the initial fingerprint matches to files notknown to be malicious that the initial fingerprint matches.
 6. Thecomputer-implemented method of claim 4, wherein the false positive rateis determined by a historical percentage of accurate matches for theinitial fingerprint.
 7. The computer-implemented method of claim 1,wherein the additional fingerprint represents a larger portion of thefile than the initial fingerprint represents.
 8. Thecomputer-implemented method of claim 1, wherein the part of the filecomprises at least one of: content within the file; a size of the file;a timestamp within the file; header data of the file.
 9. A system fordetecting malicious files: the system comprising: a determination moduleprogrammed to determine that a file previously stored on a client systemis subject to a security assessment; a generation module programmed to,based on determining that the file is subject to the securityassessment, generate an initial fingerprint of the file on the clientsystem, the generation of the initial fingerprint excluding at least apart of the file; a sending module programmed to send, from the clientsystem, the initial fingerprint to a server and a receiving moduleprogrammed to receive a response from the server comprising anindication that the initial fingerprint matches at least one knownmalicious file but that the file from which the initial fingerprint wasgenerated may not match the malicious file; where the generation moduleis further programmed to generate, in response to the indication, anadditional fingerprint of the file on the client system based at leastin part on the part of the file excluded in the generation of theinitial fingerprint; where the sending module is further programmed tosend, from the client system, the additional fingerprint to the serverand the receiving module is further programmed to receive an additionalresponse from the server indicating that the file on the client systemis malicious; where the determination module is further programmed todetermine that a second file previously stored on the client system issubject to a second security assessment; where the generation module isfurther programmed to, based on determining that the second file issubject to the second security assessment, generate a second initialfingerprint of the second file on the client system, the generation ofthe second initial fingerprint excluding at least a second part of thesecond file; where the sending module is further programmed to send,from the client system, the second initial fingerprint to the server andthe receiving module is further programmed to receive a second responsefrom the server comprising a second indication that the second initialfingerprint matches at least one malicious file; where the determinationmodule is further programmed to determine, based on the secondindication, despite the second part of the second file being excludedfrom the generation of the second initial fingerprint, and withoutgenerating a further fingerprint of the second file after generating thesecond initial fingerprint, that the second file on the client system ismalicious; at least one hardware processor configured to executesoftware comprising the determination module, the generation module, thesending module, and the receiving module.
 10. The system of claim 9, thesoftware further comprising a security module programmed to perform asecurity action on the file based on the additional response indicatingthat the file is malicious.
 11. The system of claim 10, wherein thesecurity module is programmed to perform the security action on the fileby at least one of: deleting the file; quarantining the file; alerting auser that the file is malicious.
 12. The system of claim 9, wherein theindication that the initial fingerprint matches the at least one knownmalicious file comprises a false positive rate for the initialfingerprint, the false positive rate comprising the probability that theadditional fingerprint will not match any malicious files.
 13. Thesystem of claim 12, wherein the false positive rate is determined by aratio of known malicious files that the fingerprint matches to files notknown to be malicious that the fingerprint matches.
 14. The system ofclaim 12, wherein the false positive rate is determined by a historicalpercentage of accurate matches for the initial fingerprint.
 15. Thesystem of claim 9, wherein the additional fingerprint represents alarger portion of the file than the initial fingerprint represents. 16.The system of claim 9, wherein the part of the file comprises at leastone of: content within the file; a size of the file; a timestamp withinthe file; header data of the file.
 17. A non-transitorycomputer-readable-storage medium comprising one or morecomputer-readable instructions that, when executed by at least oneprocessor of a computing device, cause the computing device to:determine that a file previously stored on a client system is subject toa security assessment; based on determining that the file is subject tothe security assessment, generate an initial fingerprint of the file onthe client system, the generation of the initial fingerprint excludingat least a part of the file; send, from the client system, the initialfingerprint to a server and receive a response from the servercomprising an indication that the initial fingerprint matches at leastone known malicious file but that the file from which the initialfingerprint was generated may not match the malicious file; generate, inresponse to the indication, an additional fingerprint of the file on theclient system based at least in part on the part of the file excluded inthe generation of the initial fingerprint; send, from the client system,the additional fingerprint to the server and receive an additionalresponse from the server indicating that the file on the client systemis malicious; determine that a second file previously stored on theclient system is subject to a second security assessment; based ondetermining that the second file is subject to the second securityassessment, generate a second initial fingerprint of the second file onthe client system, the generation of the second initial fingerprintexcluding at least a second part of the second file; send, from theclient system, the second initial fingerprint to the server and receivea second response from the server comprising a second indication thatthe second initial fingerprint matches at least one malicious file;determine, based on the second indication, despite the second part ofthe second file being excluded from the generation of the second initialfingerprint, and without generating a further fingerprint of the secondfile after generating the second initial fingerprint, that the secondfile on the client system is malicious.
 18. The non-transitorycomputer-readable-storage medium of claim 17, wherein the indicationthat the initial fingerprint matches the at least one known maliciousfile comprises a false positive rate for the initial fingerprint, thefalse positive rate comprising the probability that the additionalfingerprint will not match any malicious files.
 19. The non-transitorycomputer-readable-storage medium of claim 18, wherein the false positiverate is determined by a ratio of known malicious files that the initialfingerprint matches to files not known to be malicious that the initialfingerprint matches.
 20. The non-transitory computer-readable-storagemedium of claim 18, wherein the false positive rate is determined by ahistorical percentage of accurate matches for the initial fingerprint.